Move change to bug and rename into result and expected

Author: 1kastner

doc/source/whatsnew/v0.21.1.txt

@@ -22,7 +22,6 @@ Other Enhancements
 ^^^^^^^^^^^^^^^^^^
 
 - :meth:`Timestamp.timestamp` is now available in Python 2.7. (:issue:`17329`)
-- :class:`DatetimeIndex` is now timezone aware when using strings as labels for indexing (:issue:`16785`)
 -
 
 .. _whatsnew_0211.deprecations:
@@ -62,6 +61,7 @@ Bug Fixes
 - Bug in ``pd.Series.rolling.skew()`` and ``rolling.kurt()`` with all equal values has floating issue (:issue:`18044`)
 - Bug in ``pd.DataFrameGroupBy.count()`` when counting over a datetimelike column (:issue:`13393`)
 - Bug in ``pd.concat`` when empty and non-empty DataFrames or Series are concatenated (:issue:`18178` :issue:`18187`)
+- Bug in :class:`DatetimeIndex` when partial string label indices are actually timezone aware (:issue:`16785`)
 
 Conversion
 ^^^^^^^^^^

pandas/tests/indexing/test_partial.py

@@ -648,17 +648,16 @@ def test_access_timezoned_datetimeindex_with_timezoned_label(self):
         df = pd.DataFrame(index=first_january, data=np.arange(len(
                           first_january)))
 
-        former_naive_endpoint_df = df[
+        result = df[
             "2016-01-01T00:00-02:00":"2016-01-01T02:03"
         ]
 
-        former_non_naive_endpoint_df = df[
+        expected = df[
             pd.Timestamp("2016-01-01T00:00-02:00"):
             pd.Timestamp("2016-01-01T02:03")
         ]
 
-        tm.assert_frame_equal(former_naive_endpoint_df,
-                              former_non_naive_endpoint_df)
+        tm.assert_frame_equal(result, expected)
 
     def test_access_naive_datetimeindex_with_timezoned_label(self):
 
@@ -672,11 +671,11 @@ def test_access_naive_datetimeindex_with_timezoned_label(self):
                           first_january)))
 
         with tm.assert_produces_warning(UserWarning):
-            former_naive_endpoint_df = df["2016-01-01T00:00-02:00":
-                                          "2016-01-01T02:03"]
+            result = df["2016-01-01T00:00-02:00":"2016-01-01T02:03"]
 
-        former_non_naive_endpoint_df = df[pd.Timestamp(
-            "2016-01-01T00:00-02:00"):pd.Timestamp("2016-01-01T02:03")]
+        expected = df[
+            pd.Timestamp("2016-01-01T00:00-02:00"):
+            pd.Timestamp("2016-01-01T02:03")
+        ]
 
-        tm.assert_frame_equal(former_non_naive_endpoint_df,
-                              former_naive_endpoint_df)
+        tm.assert_frame_equal(expected, result)